The Urban Climate

Cities represent massive anthropogenic interventions in the planetary environment. They contribute to climate change and are affected by it. The world population increasingly lives in cities, implying the critical need for a better understanding of the complexity of the climatic context of urban agglomerations and their inner microclimatic characteristics. The urban microclimate is not only relevant to people's experience of outdoor thermal conditions in the cities: The temporal and spatial variance of urban microclimate is also causally related to the thermal performance of buildings. These considerations represent the main motivations behind a number of research questions addressed in this paper: To which extent do microclimatic conditions in cities differ from those in the surrounding rural environment? What physical features of the urban environment could explain the variance of urban microclimate? What measures could mitigate adverse developments in microclimatic conditions in the cities? Can computational tools and models contribute to prediction the effects of mitigation measures

Subject Assessment of Thermal Transition in a Museum: a Case Study

Thermal sensation and comfort evaluation schemes typically address thermally adapted people under static circumstances. A disregard of thermal evaluation processes pertaining to transitional states may result in inappropriate temperature settings, inefficient thermal control, and poor thermal comfort. Thus, recently studies have been carried out, which consider thermal perception under dynamic (transitional) conditions. This paper represents an example of such a study. It investigates people's subjective thermal sensation assessment immediately after a spatial transition, i.e., entering or exiting a building or moving between different spaces within a building. Field experiments were conducted in the Museum of Art History (Kunsthistorisches Museum) in Vienna, Austria. Multiple groups of participants moved through a predefined route throughout the building. This route involved five spatial transitions. Immediately after each transition, the participants expressed their thermal sensation vote (TSV) via a questionnaire. Participants' responses were analyzed in the context of monitored temperature differences between the spaces along the participants' route through the building

An empirical study of occupants' evaluation of short-term combined thermal, visual, and acoustic indoor-environmental exposure

Recently, more attention is being paid to human sensation and perception processes under multidomain indoor-environmental exposure situations. Despite the existing body of research in this area, many more studies must be conducted to elevate the level of our understanding of such processes. In this paper, we present such a study. Thereby, two identical small office units are assembled within a larger laboratory space. Thermal and visual conditions can be separately controlled in these two units. Furthermore, different acoustical conditions can be emulated in the larger laboratory space that houses the two small office units. During the experiments, participants occupy these offices and are exposed to a number of different combinations of indoor-environmental (thermal, visual, and auditory) factors. A key query thereby is as follows: Are identical thermal conditions evaluated differently given interference attributable to other exposure variables (e.g., glare, noise). The paper presents the research design and the results.publishedVersio

Monitoring-based optimization-assisted calibration of the thermal performance model of an office building

This paper reports on a case study of monitoring-based optimization-assisted calibration of a thermal simulation model for an office building. Such a calibrated model could effectively support the operation of the building. For example, it could be deployed toward diagnostics, fault detection, preventive maintenance, and a model-based building systems control. To explore the potential of optimization-assisted calibration in a realistic setting, we selected an actual office. This facility is equipped with a monitoring infrastructure, which provides various streams of data about outdoor and building conditions. Our intention was to deploy data obtained via the monitoring system to both populate the initial simulation model and to maintain its fidelity through a systematic calibration process. The initial simulation model used, asides from static physical building information, dynamic monitored data including electrical plug loads, occupancy, and state of devices such as luminaires and windows. In the optimization-assisted calibration, a weighted cost function was defined, which addressed the bias error between measured and simulated indoor temperature and the goodness of fit of the model. A limited number of model input parameters were varied in the optimization process toward minimizing the cost function. The resulting calibrated model showed noticeable accuracy improvement and the optimization-assisted method displayed a promising potential as a systematic calibration method in model-based predictive systems control

Optimization-based simulation model calibration using sensitivity analysis

This paper examines the potential of sensitivity analysis-assisted optimization-based simulation model calibration. Toward this end, a university campus office area was selected and equipped with a monitoring infrastructure. Various streams of data were collected, including indoor climate, outdoor weather conditions, energy delivery via the building's heating system, and energy use for lighting and equipment. One of the primary objectives of this comprehensive monitoring campaign was to use monitored data to both populate the initial thermal simulation model of the office area and to maintain its fidelity through a calibration process. The present contribution also addresses a specific problem faced by an optimization-based simulation calibration approach: In many realistic circumstances, a large number of model input variables could be subjected to the optimization process. This large number of candidate input variables can be reduced to a certain extent via heuristicallybased considerations pertaining, for example, to the knowledge domain captured in building physics. We argue, however, that this process could be further rationalized, if we make use of sensitivity analysis to identify a subset of the input variables most likely to influence the simulation results. Distinguishing this subset from the entire set of input variables will reduce the computational cost of the subsequent calibration process

Testing a Method for the Generation of the Systems Control Schemes for Buildings

In previous publications, a method was introduced to derive a general scheme for the distribution of the control logic regarding systems control and automation in complex buildings. This scheme is generated based two initial layers of information pertaining to an architectural space. The first layer enumerates the different zones in the space that are targeted for environmental control via heating, cooling, ventilation, illumination, etc. Each zone is represented via a sensor that monitors the state of that zone. The second layer enumerated all the devices (and their respective terminals) that are intended to control the zone via introduction or removal of some amount of energy or mass (e.g., windows, blinds, luminaires, diffusors, radiators). To empirically explore the viability of the scheme generation method, a test was conducted involving a number of architecture and engineering students. Thereby, the information for the generation of scheme was collected and documented for a number of actual spaces. Subsequently, the scheme generation method was deployed to generate for each case a general scheme for the distribution of control logic. The results of the experiment and their implications for the further development and application of the method are discussed

Can we measure buildings' affordance?

The term affordance is used in this paper to denote the capacity of buildings to provide occupants the possibility to control the indoor-environmental conditions so as to meet their needs and requirements. This is typically facilitated via buildings’ various control devices and systems meant to control ambient conditions. In this paper, we discuss recent progress in developing a building affordance evaluation method. The idea is to evaluate buildings’ control devices and elements based on their availability as well as their effectiveness. We critically examine the strengths and weaknesses of the proposed affordance measurement method and discuss its future potential to be used as a performance assessment tool by professionals and stakeholders in building design and operation.publishedVersio

Computational assessment of the energy performance of a predictive simulation-based lighting and shading systems control approach in buildings

This paper presents a daylight-responsive predictive lighting and shading systems control in buildings that makes use of real-time sensing and lighting simulation. This system can control the position of window blinds and the status of the luminaires. Specifically, the paper compares the performance of this predictive simulation-based lighting and shading systems control method with five other – more conventional – control methods. All six options are virtually implemented and tested in an office building. The performance comparison considers electrical energy use for lighting as well as visual performance criteria (illuminance, UGR). The results of the virtual implementation and comparison of these control methods demonstrate the significant potential of the predictive simulation-assisted lighting systems control method toward reducing electrical energy use for lighting in office buildings, while offering satisfactory visual performance

A Comparative Performance Study of Diffuse Fraction Models Based on Data from Vienna, Austria

Computational applications for the evaluation of buildings' energy performance (including their passive and active solar energy systems) require detailed information regarding incident solar radiation. As only global horizontal irradiance data is available for most locations, models are needed to derive from such global data, the diffuse radiation component. In this context, the present paper compares the predictive performance of six existing and one new diffuse fraction models for the location of Vienna, Austria